The oral cavity microbiota: between health, oral disease, and cancers of the aerodigestive tract
Bibliographic record
Abstract
Many studies show that the human microbiome plays a critical role in the chronic pathologies of obesity, inflammatory bowel diseases, and diabetes. More recently, the interaction between cancer and the microbiome has been highlighted. Most studies have focused on the gut microbiota because it represents the most extensive bacterial community, and the body of evidence correlating it with gut syndromes is increasing. However, in the strict sense, the gastrointestinal (GI) tract begins in the oral cavity, and special attention should be paid to the specific flora of this cavity. This study reviewed the current knowledge about the various microbial ecosystems of the upper part of the GI tract and discussed their potential link to carcinogenesis. The overall composition of the microbial communities, as well as the presence or absence of "key species", in relation to carcinogenesis is addressed. Alterations in the oral microbiota can potentially be used to predict the risk of cancer. Molecular advances and the further monitoring of the microbiota will increase our understanding of the role of the microbiota in carcinogenesis and open new perspectives for future therapeutic and prophylactic modalities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".